16 citations · 17 across the 3 of their papers we have counts for
5 papers
Qwen3-VL Technical Report
Shuai Bai, Yuxuan Cai, Ruizhe Chen +61
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…
BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses
Xin Xu, Xunzhi He, Churan Zhi +3
Existing studies on bias mitigation methods for large language models (LLMs) use diverse baselines and metrics to evaluate debiasing performance, leading to inconsistent comparison…
RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark
Yang Shi, Yuhao Dong, Yue Ding +22
The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question rem…
BiasFilter: An Inference-Time Debiasing Framework for Large Language Models
Xiaoqing Cheng, Ruizhe Chen, Hongying Zan +2
Mitigating social bias in large language models (LLMs) has become an increasingly important research objective. However, existing debiasing methods often incur high human and compu…
Performance Evaluation of Large Language Models in Statistical Programming
Xinyi Song, Kexin Xie, Lina Lee +10
The programming capabilities of large language models (LLMs) have revolutionized automatic code generation and opened new avenues for automatic statistical analysis. However, the v…